A method and device for tone-mapping a picture by using a parametric tone-adjustment function

ABSTRACT

The present principles relates to a method and device for tone-mapping an input picture by using a parametric tone-adjustment function. The method is characterized in that the method comprises determining at least one parameter of said tone-adjustment function modulated by a brightness level of the input picture.

3. FIELD

The present principles generally relate to picture/video tone-mapping.Particularly, but not exclusively, the technical field of the presentprinciples are related to tone-mapping a picture whose pixels valuesbelong to a high-dynamic range.

2. BACKGROUND

The present section is intended to introduce the reader to variousaspects of art, which may be related to various aspects of the presentprinciples that are described and/or claimed below. This discussion isbelieved to be helpful in providing the reader with backgroundinformation to facilitate a better understanding of the various aspectsof the present principles. Accordingly, it should be understood thatthese statements are to be read in this light, and not as admissions ofprior art.

In the following, a picture contains one or several arrays of samples(pixel values) in a specific picture/video format which specifies allinformation relative to the pixel values of a picture (or a video) andall information which may be used by a display and/or any other deviceto visualize and/or decode a picture (or video) for example. A picturecomprises at least one component, in the shape of a first array ofsamples, usually a luma (or luminance) component, and, possibly, atleast one other component, in the shape of at least one other array ofsamples, usually a color component. Or, equivalently, the sameinformation may also be represented by a set of arrays of color samples,such as the traditional tri-chromatic RGB representation.

A pixel value is represented by a vector of C values, where C is thenumber of components. Each value of a vector is represented with anumber of bits which defines a maximal dynamic range of the pixelvalues.

Standard-Dynamic-Range pictures (SDR pictures) are color pictures whoseluminance values are represented with a limited dynamic usually measuredin power of two or f-stops. SDR pictures have a dynamic around 10f-stops, i.e. a ratio 1000 between the brightest pixels and the darkestpixels in the linear domain, and are coded with a limited number of bits(most often 8 or 10 in HDTV (High Definition Television systems) andUHDTV (Ultra-High Definition Television systems) in a non-linear domain,for instance by using the ITU-R BT.709 OEFT(Optico-Electrical-Transfer-Function) (Rec. ITU-R BT.709-5, April 2002)or ITU-R BT.2020 OETF (Rec. ITU-R BT.2020-1, June 2014) to reduce thedynamic. This limited non-linear representation does not allow correctrendering of small signal variations, in particular in dark and brightluminance ranges. In High-Dynamic-Range pictures (HDR pictures), thesignal dynamic is much higher (up to 20 f-stops, a ratio one millionbetween the brightest pixels and the darkest pixels) and a newnon-linear representation is needed in order to maintain a high accuracyof the signal over its entire range. In HDR pictures, raw data areusually represented in floating-point format (either 32-bit or 16-bitfor each component, namely float or half-float), the most popular formatbeing openEXR half-float format (16-bit per RGB component, i.e. 48 bitsper pixel) or in integers with a long representation, typically at least16 bits. More compact representation do exist like, for instance, the 10or 12 bit format obtained by using the so-called PQ OETF defined inSMPTE 2084 (SMPTE standard: High Dynamic Range Electro-Optical TransferFunction of Mastering Reference Displays, SMPTE ST 2084:2014).

Tone-mapping is a well-known operation that reduces the dynamic range ofan input picture.

A tone-mapping operation may be implemented as a tone adjustmentfunction which determines an output SDR value for each input HDR valueor reciprocally.

FIG. 1 shows an example of a tone-adjustment function (representedgraphically by a curve) as defined in “Philips HDR proposal Dynamicrange conversion in relation to the “Unified Model” as discussed inSMPTE DG “Dynamic Metadata for Color Transforms of HDR and WCG Images”R. Nijland Koninklijke Philips N.V. 20150421.

The tone-adjustment function is a parametric tone-adjustment functiondefined on three ranges (time intervals): the bottom interval, themid-interval and the upper interval.

Over the bottom interval, the tone-adjustment function is linear:y=SGC*x with SGC a real parameter value, y an output value and x aninput value.

Over the upper interval, the tone-adjustment function is also linear:y=HGC*x+(1−HGC) with HGC a slope (real parameter value).

Over the mid-interval, the tone-adjustment function is a parabolaax²+bx+c, x_(SGC) connecting the two linear intervals in a smoothcross-over. The width of the cross-over is determined by MTA, a realparameter value.

$\begin{matrix}{y = \{ \begin{matrix}{{{SGC} \cdot x},{0 \leq x \leq x_{SGC}}} \\{{{ax}^{2} + {bx} + c},{x_{{SGC}\;} < x < x_{HGC}}} \\{{{{HGC} \cdot x} + 1 - {HGC}},{x_{HGC} \leq x \leq 1}}\end{matrix} } & (1) \\{where} & \; \\\{ \begin{matrix}{a = {{{- 0.5} \cdot {SGC}} - {{HGC}\mspace{14mu} {MTA}}}} \\{b = {\frac{1 - {HGC}}{MTA} + \frac{{SGC} + {HGC}}{2}}} \\{c = {\frac{1 - {HGC}}{{SGC} - {HGC}} + \frac{MTA}{2}}}\end{matrix}  & (2) \\{and} & \; \\\{ \begin{matrix}{x_{SGC} = {\frac{1 - {HGC}}{{SGC} - {HGC}} - \frac{MTA}{2}}} \\{x_{HGC} = {\frac{1 - {HGC}}{{SGC} - {HGC}} + \frac{MTA}{2}}}\end{matrix}  & (3)\end{matrix}$

According to this prior art, the parameters SGC, HGC and MTA parametervalues depend on the three input parameter values shadowGainControl,midTonesAdjustement and highlightGainControl as follows:

$\begin{matrix}\{ \begin{matrix}{{{exposure} = {\frac{shadowGainControl}{4} + 0}},5} \\{{expgain} = {v( \frac{L_{source}}{L_{target}} )}} \\{{SGC} = {{expgain}.\; {exposure}}} \\{{HGC} = \frac{highLightGainControl}{4}} \\{{MTA} = \frac{midTonesAdjustement}{2}}\end{matrix}  & (4) \\{{{with}\mspace{14mu} {v(x)}} = {{\frac{\log ( {1 + {( {\rho - 1} ).x^{\frac{1}{\gamma}}}} )}{\log (\rho)}\mspace{14mu} {and}\mspace{14mu} \rho} = {1 + {32.\; ( \frac{L_{target}}{10000} )^{1/\gamma}}}}} & \;\end{matrix}$

For example, in the above equations, L_(target) is equal to 100 nits,L_(source) is preferably equal to 4000 nits or 5000 nits and thefunction v is the identity function.

As a consequence, three input parameters shadowGainControl,highLightGainControl and midTonesAdjustement have to be given to specifythe tone-adjustment function, which is piecewise linear and parabolic.

The present disclosure is not limited to a specific parametric toneadjustment function.

The input parameters specifying a parametric tone-adjustment functionmay be manually chosen according to one's artistic intent but this makesit difficult to configure an automated tone-mapping method in a properand robust way across many video contents for defining these parameters.

3. SUMMARY

The following presents a simplified summary of the present principles inorder to provide a basic understanding of some aspects of the presentprinciples. This summary is not an extensive overview of the presentprinciples.

It is not intended to identify key or critical elements of the presentprinciples. The following summary merely presents some aspects of thepresent principles in a simplified form as a prelude to the moredetailed description provided below.

The present principles set out to remedy at least one of the drawbacksof the prior art with a method for tone-mapping an input picture byusing a parametric tone-adjustment function defined over multipleranges, at least one parameter of the tone-adjustment function beingassociated to each range. The method comprises defining a non-lineartone adjustment function over at least one range, and determining atleast one parameter of said tone-adjustment function modulated by abrightness level of the input picture.

In accordance with an example of the present principles, the toneadjustment function is defined over three ranges.

In accordance with an example of the present principles, the toneadjustment function is linear over a first range, parabolic over asecond range and linear over a third range.

In accordance with an example of the present principles, the toneadjustment function is defined:

over the first range by:

y=SGC*x

with SGC a real parameter value, y an output value and x an input value;

over the second range by:

ax ² +bx+c, x _(SGC) <x<x _(HGC)

over the third range by:

y=HGC*x+(1−HGC)

with HGC a slope;

-   where

$\{ {\begin{matrix}{a = {{{- 0.5} \cdot {SGC}} - {{HGC}\mspace{14mu} {MTA}}}} \\{b = {\frac{1 - {HGC}}{MTA} + \frac{{SGC} + {HGC}}{2}}} \\{c = {\frac{1 - {HGC}}{{SGC} - {HGC}} + \frac{MTA}{2}}}\end{matrix}\{ \begin{matrix}{x_{SGC} = {\frac{1 - {HGC}}{{SGC} - {HGC}} - \frac{MTA}{2}}} \\{x_{HGC} = {\frac{1 - {HGC}}{{SGC} - {HGC}} + \frac{MTA}{2}}}\end{matrix} } $

with MTA, a real parameter value and

$\begin{matrix}\{ \begin{matrix}{{{exposure} = {\frac{shadowGainControl}{4} + 0}},5} \\{{expgain} = {{v( \frac{L_{source}}{L_{target}} )}\mspace{14mu} {with}\mspace{14mu} v\mspace{14mu} a\mspace{14mu} {function}\mspace{14mu} {based}\mspace{14mu} {on}\mspace{14mu} L_{target}}} \\{{SGC} = {{expgain}.{exposure}}} \\{{HGC} = \frac{highLightGainControl}{4}} \\{{MTA} = \frac{midTonesAdjustement}{2}}\end{matrix}  \\{{{with}\mspace{14mu} {v(x)}} = {{\frac{\log ( {1 + {( {\rho - 1} ).x^{\frac{1}{\gamma}}}} )}{\log (\rho)}\mspace{14mu} {and}\mspace{14mu} \rho} = {1 + {32.\; ( \frac{L_{target}}{10000} )^{1/\gamma}}}}}\end{matrix}$

where shadowGainControl, and midTonesAdjustement are real values givenby:

$\{ {\begin{matrix}{{shadowGainControl} = {0.229 + {2.47*{\exp ( {{- 0.333}*{Ba}} )}}}} \\{{midTonesAdjustement} = {2.21*{\exp ( {{- 0.16}*{Ba}} )}}}\end{matrix}\quad} $

where highlightGainControl is a real value and a modulation value Baresponsive to a brightness level of the input picture and expressed innits.

In accordance with an example of the present principles, the real valuehighlightGainControl is is a constant value.

In accordance with an example of the present principles, the real valuehighlightGainControl is kept as another parameter in addition to themodulation value.

In accordance with an example of the present principles, the real valuehighlightGainControl is given by:

highlightGainControl=2−2*exp(−0.26/Ba)

In accordance with an example of the present principles, the toneadjustment function is defined:

over the first range by:

$y = {{SGC}^{\prime}*\frac{x}{Ba}}$

with SGC a real parameter value, y an output value and x an input value;

over the second range by:

$y = {{a^{\prime}( \frac{x}{Ba} )}^{2} + {b^{\prime}\frac{x}{Ba}} + c^{\prime}}$

over the third range by:

$y = {{{HGC}^{\prime}*\frac{x}{Ba}} + ( {1 - \frac{{HGC}^{\prime}}{Ba}} )}$

with HGC a slope;

-   where

$\{ {\begin{matrix}{a^{\prime} = {{Ba}.( {{{- 0.5} \cdot {SGC}^{\prime}} - {{HGC}^{\prime}.{MTA}^{\prime}}} )}} \\{b^{\prime} = {\frac{{Ba} - {HGC}^{\prime}}{{MTA}^{\prime}} + \frac{{SGC}^{\prime} + {HGC}^{\prime}}{2}}} \\{c^{\prime} = {\frac{{Ba} - {HGC}^{\prime}}{{SGC}^{\prime} - {HGC}^{\prime}} + \frac{{MTA}^{\prime}}{2}}}\end{matrix}\{ \begin{matrix}{x_{SGC}^{\prime} = {\frac{B_{a} - {HGC}^{\prime}}{{SGC}^{\prime} - {HGC}^{\prime}} - \frac{{MTA}^{\prime}}{2}}} \\{x_{HGC}^{\prime} = {\frac{B_{a} - {HGC}^{\prime}}{{SGC}^{\prime} - {HGC}^{\prime}} - \frac{{MTA}^{\prime}}{2}}}\end{matrix} } $

with MTA, a real parameter value and

$\{ {{\begin{matrix}{{expgain} = {v( \frac{L_{source}}{L_{target}} )}} \\{{SGC}^{\prime} = {expgain}} \\{{HGC}^{\prime} = \frac{highLightGainControl}{4}} \\{{MTA}^{\prime} = \frac{midTonesAdjustment}{2}}\end{matrix}{with}\mspace{14mu} {v(x)}} = {{\frac{\log ( {1 + {( {\rho - 1} ).x^{\frac{1}{\gamma}}}} )}{\log (\rho)}\mspace{14mu} {and}\mspace{14mu} \rho} = {1 + {32.( \frac{L_{target}}{100000} )^{1/\gamma}}}}} $

where midTonesAdjustement is a real value given by :

$\quad\{ \begin{matrix}{{midTonesAdjustement} = {2.21*{\exp ( {{- 0.16}*{Ba}} )}}} \\{{highlightGainControl} = {CST}}\end{matrix} $

where highlightGainControl is a real value and a modulation value Baresponsive to a brightness level of the input picture and expressed innits.

In accordance with an example of the present principles, thetone-adjustment function is a parametric logarithm function defined by:

ba_(N) = Ba/PeakL$N = {\log ( {1 + \frac{1}{k.{ba}_{N}}} )}$${y = \frac{\log ( {1 + \frac{x}{k.{ba}_{N}}} )}{N}},{\forall{x \in \lbrack {0,1} \rbrack}}$

with k a constant value, y an output value and x an input value andPeakL the peak luminance value of the input picture.

In accordance with an example of the present principles, the modulationvalue is responsive to a mid-tone level of the input picture.

In accordance with an example of the present principles, the mid-tonelevel is determined based on a black level and a white level.

In accordance with an example of the present principles, the mid-tonelevel is determined as one of (1) a geometric mean and (2) a logarithmmean of the black level and the white level.

In accordance with an example of the present principles, the input imageis one of a plurality of pictures included in a video sequence, andwherein the determining of the modulation value is performed for each ofthe plurality of pictures, wherein the modulation values for theplurality of pictures are temporally smoothed.

According to another of its aspects, the present disclosure relates to amethod for inverse-tone-mapping a tone-mapped version of an inputpicture by using a parametric inverse-tone-adjustment function definedover multiple ranges, at least one parameter of the tone-adjustmentfunction being associated to each range. The method is characterized inthat the method comprises defining a non-linear tone adjustment functionover at least one range, and obtaining at least one parameter of theinverse-tone-adjustment function modulated by a brightness level of theinput picture.

According to another of its aspects, the present disclosure relates to amethod for encoding an input picture comprising:

obtaining a maximum value from the component values of the inputpicture;

obtaining a linear value by tone-mapping said maximum value according toa above method;

multiplying the input picture by a ratio between the linear value overthe maximum value.

According to another of its aspects, the present disclosure relates to amethod for decoding a picture comprising:

obtaining a maximum value from the component values of a decodedpicture;

obtaining a non-linear value by inverse-tone-mapping said maximum valueaccording to a above method;

multiplying the decoded picture by a ratio between the non-linear valueover the maximum value.

According to another of its aspects, the present disclosure relates to adevice for tone-mapping an input picture by using a parametrictone-adjustment function defined over multiple ranges, at least oneparameter of the tone-adjustment function being associated to eachrange, characterized in that the device comprises a processor configuredto define a non-linear tone adjustment function over at least one range,and determine at least one parameter of said tone-adjustment functionmodulated by a brightness level of the input picture.

According to another of its aspects, the present disclosure relates to adevice for encoding an input picture comprising a processor configuredto:

obtain a maximum value from the component values of the input picture;

obtain a linear value by tone-mapping said maximum value according to aabove method;

multiply the input picture by a ratio between the linear value over themaximum value.

According to another of its aspects, the present disclosure relates to adevice for decoding a picture comprising a processor configured to:

obtain a maximum value from the component values of a decoded picture;

obtain a non-linear value by inverse-tone-mapping said maximum valueaccording to a above method;

multiply the decoded picture by a ratio between the non-linear valueover the maximum value.

According to another of its aspects, the present disclosure relates to asignal carrying an encode picture, characterized in that it furthercarries an information data indicating a modulation value responsive toa brightness level of the encoded input picture.

According to other of their aspects, the present principles relate to acomputer program product comprising program code instructions to executethe steps of the above method when this program is executed on acomputer, and a non-transitory storage medium carrying instructions ofprogram code for executing steps of the above method when said programis executed on a computing device.

The specific nature of the present principles as well as other objects,advantages, features and uses of the present principles will becomeevident from the following description of examples taken in conjunctionwith the accompanying drawings.

4. BRIEF DESCRIPTION OF DRAWINGS

In the drawings, examples of the present principles are illustrated. Itshows:

FIG. 1 shows an example of a tone-adjustment function in accordance withprior art;

FIG. 2 shows a diagram of the steps of the method for tone-mapping aninput picture in accordance with an example of the present principles;

FIG. 3 shows an example of a histogram depending on the linear luminanceY of an input picture in accordance with the prior art;

FIG. 4-5 illustrated how to determine a modulation value;

FIG. 6 shows a diagram of the steps of the method forinverse-tone-mapping an input picture in accordance with an example ofthe present principles;

FIG. 7 illustrates the overall method for encoding HDR content inaccordance with an example of the present principles;

FIG. 8 illustrates the overall method for decoding HDR content inaccordance with an example of the present principles;

FIG. 9 shows the sub-steps of the dynamic range conversion in accordancewith an example of the present principles;

FIG. 10 shows the sub-steps of the inverse dynamic range reduction inaccordance with an example of the present principles;

FIG. 11 shows a diagram of the steps of obtaining a linear value t bytone mapping a maximum value T in accordance with an example of thepresent principles;

FIG. 12 shows an example of an architecture of a device in accordancewith an example of present principles; and

FIG. 13 shows two remote devices communicating over a communicationnetwork in accordance with an example of present principles;

FIG. 14 shows the syntax of a signal in accordance with an example ofpresent principles.

Similar or same elements are referenced with the same reference numbers.

6. DESCRIPTION OF EXAMPLE OF THE PRESENT PRINCIPLES

The present principles will be described more fully hereinafter withreference to the accompanying figures, in which examples of the presentprinciples are shown. The present principles may, however, be embodiedin many alternate forms and should not be construed as limited to theexamples set forth herein. Accordingly, while the present principles aresusceptible to various modifications and alternative forms, specificexamples thereof are shown by way of examples in the drawings and willherein be described in detail. It should be understood, however, thatthere is no intent to limit the present principles to the particularforms disclosed, but on the contrary, the disclosure is to cover allmodifications, equivalents, and alternatives falling within the spiritand scope of the present principles as defined by the claims.

The terminology used herein is for the purpose of describing particularexamples only and is not intended to be limiting of the presentprinciples. As used herein, the singular forms “a”, “an” and “the” areintended to include the plural forms as well, unless the context clearlyindicates otherwise. It will be further understood that the terms“comprises”, “comprising,” “includes” and/or “including” when used inthis specification, specify the presence of stated features, integers,steps, operations, elements, and/or components but do not preclude thepresence or addition of one or more other features, integers, steps,operations, elements, components, and/or groups thereof. Moreover, whenan element is referred to as being “responsive” or “connected” toanother element, it can be directly responsive or connected to the otherelement, or intervening elements may be present. In contrast, when anelement is referred to as being “directly responsive” or “directlyconnected” to other element, there are no intervening elements present.As used herein the term “and/or” includes any and all combinations ofone or more of the associated listed items and may be abbreviated as“/”.

It will be understood that, although the terms first, second, etc. maybe used herein to describe various elements, these elements should notbe limited by these terms. These terms are only used to distinguish oneelement from another. For example, a first element could be termed asecond element, and, similarly, a second element could be termed a firstelement without departing from the teachings of the present principles.

Although some of the diagrams include arrows on communication paths toshow a primary direction of communication, it is to be understood thatcommunication may occur in the opposite direction to the depictedarrows.

Some examples are described with regard to block diagrams andoperational flowcharts in which each block represents a circuit element,module, or portion of code which comprises one or more executableinstructions for implementing the specified logical function(s). Itshould also be noted that in other implementations, the function(s)noted in the blocks may occur out of the order noted. For example, twoblocks shown in succession may, in fact, be executed substantiallyconcurrently or the blocks may sometimes be executed in the reverseorder, depending on the functionality involved.

Reference herein to “in accordance with an example” or “in an example”means that a particular feature, structure, or characteristic describedin connection with the example can be included in at least oneimplementation of the present principles. The appearances of the phrasein accordance with an example” or “in an example” in various places inthe specification are not necessarily all referring to the same example,nor are separate or alternative examples necessarily mutually exclusiveof other examples.

Reference numerals appearing in the claims are by way of illustrationonly and shall have no limiting effect on the scope of the claims.

While not explicitly described, the present examples and variants may beemployed in any combination or sub-combination.

In accordance with the present principles, illustrated in FIG. 2, amethod for tone-mapping an input picture I by using a parametrictone-adjustment function TAF comprises determining at least oneparameter of the tone-adjustment function TAF responsive to a modulationvalue Ba, itself responsive to a brightness level of the input picture.

In accordance with a first example of the present principles,illustrated FIG. 1, the tone-adjustment function TAF is the parametrictone-adjustment function given by equations (1), (2) and (3) whose twoinput parameters shadowGainControl and midTonesAdjustement aredetermined from the modulation value Ba as follows:

$\begin{matrix}\{ \begin{matrix}{{shadowGainControl} = {0.229 + {2.47*{\exp ( {{- 0.333}*{Ba}} )}}}} \\{{midTonesAdjustement} = {2.21*{\exp ( {{- 0.16}*{Ba}} )}}} \\{{highlightGainControl} = {CST}}\end{matrix}  & (5)\end{matrix}$

The input parameter highlightGainControl equals a constant value CST,for example CST=2, that do not depends on the modulation value Ba.

In accordance with a variant of the first example, the input parameterhighlightGainControl is kept as another parameter in addition to themodulation value Ba.

In accordance with a variant of the first example, the input parameterhighlightGainControl depends on the modulation value Ba as follows:

highlightGainControl=2−2*exp(−0.26/Ba

In this first example and its variants, the modulation value Ba isexpressed in nits and typically lies in the interval [1, 40].

According to this first example and its variants, the parameters SGC,HGC and MTA are then obtained from these three input parametersaccording to equation (4).

In accordance with a second example of the present principles,illustrated in FIG. 1, the tone-adjustment function TAF is a parametrictone-adjustment defined on three distinct ranges: the bottom interval,the mid-interval and the upper interval.

Over the bottom interval, the tone adjustment function is linear:

$y = {{SGC}^{\prime}*\frac{x}{Ba}}$

with SGC a real parameter value, y an output value and x an input value.

Over the upper interval, the tone adjustment function is also linear:

$y = {{{HGC}^{\prime}*\frac{x}{Ba}} + ( {1 - \frac{{HGC}^{\prime}}{Ba}} )}$

with HGC a slope (real parameter value).

Over the mid-interval, the tone adjustment function is a parabola

${a^{\prime}( \frac{x}{Ba} )}^{2} + {b^{\prime}\frac{x}{Ba}} + c^{\prime}$

connecting the two linear sections in a smooth cross-over. The width ofthe cross-over is determined by MTA, a real parameter value.

In brief, the tone adjustment function TAF is defined by:

$\begin{matrix}{y = \{ {\begin{matrix}{{{SGC}^{\prime} \cdot \frac{x}{Ba}},{0 \leq x \leq x_{SGC}^{\prime}}} \\{{{a^{\prime}( \frac{x}{Ba} )}^{2} + {b^{\prime}\frac{x}{Ba}} + c^{\prime}},{x_{SGC}^{\prime} < x < x_{HGC}^{\prime}}} \\{{{{HGC}^{\prime} \cdot \frac{x}{Ba}} + 1 - \frac{{HGC}^{\prime}}{Ba}},{x_{HGC}^{\prime} \leq x \leq 1}}\end{matrix}{where}} } & (6) \\\{ {\begin{matrix}{a^{\prime} = {{Ba}.( {{{- 0.5} \cdot {SGC}^{\prime}} - {{HGC}^{\prime}.{MTA}^{\prime}}} )}} \\{b^{\prime} = {\frac{{Ba} - {HGC}^{\prime}}{{MTA}^{\prime}} + \frac{{SGC}^{\prime} + {HGC}^{\prime}}{2}}} \\{c^{\prime} = {\frac{{Ba} - {HGC}^{\prime}}{{SGC}^{\prime} - {HGC}^{\prime}} + \frac{{MTA}^{\prime}}{2}}}\end{matrix}{and}}  & (7) \\\{ \begin{matrix}{x_{SGC}^{\prime} = {\frac{B_{a} - {HGC}^{\prime}}{{SGC}^{\prime} - {HGC}^{\prime}} - \frac{{MTA}^{\prime}}{2}}} \\{x_{HGC}^{\prime} = {\frac{B_{a} - {HGC}^{\prime}}{{SGC}^{\prime} - {HGC}^{\prime}} - \frac{{MTA}^{\prime}}{2}}}\end{matrix}  & (8)\end{matrix}$

In accordance with a variant of this second example, the parametersSGC′, HGC′ and MTA′ parameter values depend on two input parametervalues midTonesAdjustement and highlightGainControl as follows:

$\begin{matrix}\{ {{\begin{matrix}{{expgain} = {v( \frac{L_{source}}{L_{target}} )}} \\{{SGC}^{\prime} = {expgain}} \\{{HGC}^{\prime} = \frac{highLightGainControl}{4}} \\{{MTA}^{\prime} = \frac{midTonesAdjustment}{2}}\end{matrix}{with}\mspace{14mu} {v(x)}} = {{\frac{\log ( {1 + {( {\rho - 1} ).x^{\frac{1}{\gamma}}}} )}{\log (\rho)}\mspace{14mu} {and}\mspace{14mu} \rho} = {1 + {32.( \frac{L_{target}}{100000} )^{1/\gamma}}}}}  & (9)\end{matrix}$

For example, in the above equations, L_(target) is equal to 100 nits,L_(source) is preferably equal to 4000 nits or 5000 nits and v theidentity function.

In accordance with a variant of this second example, the inputparameters midTonesAdjustement is determined from the modulation valueBa as follows:

$\quad\{ \begin{matrix}{{midTonesAdjustement} = {2.21*{\exp ( {{- 0.16}*{Ba}} )}}} \\{{highlightGainControl} = {CST}}\end{matrix} $

The input parameter highlightGainControl equals a constant value CST,for example CST=2.

In accordance with a variant of the second example, the input parameterhighlightGainControl is kept as another parameter in addition to themodulation value Ba.

In accordance with a variant of the second example, the input parameterhighlightGainControl depends on the modulation value Ba as follows:

highlightGainControl=2'2*exp(−0.26/Ba)

In this second example and its variants, the modulation value Ba isexpressed in nits and lies preferably in the interval [1, 40].

In accordance with third example of the present principles, the toneadjustment function TAF is a parametric logarithm defined by:

$\begin{matrix}\{ \begin{matrix}{{ba}_{N} = {{Ba}/{PeakL}}} \\{N = {\log ( {1 + \frac{1}{k.{ba}_{N}}} )}} \\{{y = \frac{\log ( {1 + \frac{x}{k.{ba}_{N}}} )}{N}},{\forall{x \in \lbrack {0,1} \rbrack}}}\end{matrix}  & (12)\end{matrix}$

where k is a constant value, for example equal to 1000 and PeakL thepeak luminance value of the input picture.

In according with an example of the present principles, the modulationvalue Ba is obtained as follows: The pixels of the input picture areclassified into a histogram depending on their linear luminance Y, asshown in an exemplary histogram in FIG. 3. As shown in FIG. 3, therightmost of the histogram is at peak luminance P. This luminance peakis assumed to be provided, for example, based on the picture format, andnot to vary from picture to picture when a video is tone-mapped. Next, awhite level W is defined as the luminance level corresponding to thelast percentile of the histogram, a black level B is defined as theluminance level corresponding to the first percentile of the histogram,and a mid-tone level M is defined as the geometric mean (or logarithmicmean) of the black level B and the white level W:

M:=√{square root over (BW)}  (13)

As a consequence, the three levels W, B and M depend on the content ofthe input picture.

In general, the choice of the modulation value Ba and the toneadjustment function should preserve information at the very dark leveland also preserve details in the mid-tone range (i.e., the neighborhoodof the mid-tone value). Thus, two conditions are used when deriving themodulation value Ba: (1) the blacks are not clipped down to zero tooaggressively; and (2) the number of codewords in the SDR picture used torepresent the mid-tone range of the input image is maximized.

Considering the first condition that blacks should not be clipped downto zero too aggressively, a lower bound for the black level is set,i.e.,

π_(Ba)(B)≥ϵ  (14)

where π_(Ba)(.) is the tone-adjustment function, B a luminance value andϵ is a parameter value.

In FIG. 4, an exemplary a tone-adjustment function π_(Ba) is used toillustrate that the mapped value π_(Ba)(B) is set to ϵ. The inequality(14) does not determine a specific modulation value Ba. Instead, itprovides a range of acceptable modulation values for Ba.

For the second condition (the number of codewords used to encode themid-tone range should be maximized), the slope for the tone-adjustmentfunction π_(Ba) at the mid-tone level M is maximized as shown in FIG. 5.

Combining both conditions, the modulation value Ba can be uniquelydetermined by solving the following maximization problem:

$\begin{matrix}{{Ba} = {{argmax}_{\{{{{Ba}^{\prime}\mspace{14mu} {s.t.\mspace{14mu} {\pi_{{Ba}^{\prime}}{(B)}}}} \geq ɛ}\}}\frac{\partial\pi_{{Ba}^{\prime}}}{{\partial\ln}\; Y}{(M).}}} & (15)\end{matrix}$

To solve the optimization problem (15) given a tone-adjustment function,a systematic brute-force search of Ba in the range of acceptable Bavalues may be performed to compute the modulation value Ba for eachpicture of a video for example. The tone-adjustment function can be theone illustrated in FIG. 1, and the present principles can be applied toany other forms of tone-adjustment function. In Eq. (15), a log-scale isused for luminance Y as it may represent the human luminance perceptionbetter than the linear domain. In a variation, one may determine theslope based on Y instead of ln Y for simplicity. In other examples ofthe present principles, different methods can be used to determine themodulation value, for example, but not limited to, using an average,median, minimum or maximum value of the luminance of the picture I.These operations may be performed in the linear luminance domain or in anon-linear domain such as ln(I) or I^(γ) with γ<1.

To further improve the tone-adjustment functions (curves), some boundscan be imposed on the modulation value Ba in order to avoidover-shooting in both very dark frames (Ba too low) and very brightframes (Ba too high). For example, the modulation value Ba is set to

Ba _(att) =Clip _([Ba) _(min) _(,Ba) _(max]) Ba _(mid)+σ(Ba−Ba _(mid))  (16)

to determine an attenuated modulation value Ba_(att), with visuallydetermined values Ba_(min)=2 nits, Ba_(max)=50 nits, Ba_(mid)=5 nits andthe attenuation factor σ=0.5. This may provide modulation values closerto visually optimal ones.

In a video sequence, a modulation value Ba may be determined for eachpicture of said video sequence. In order to avoid temporal inconsistencyin scenes with rapid brightness changes, a temporal stabilization isdesirable. Fast changing videos, like a scene showing an explosion orfireworks, may cause modulation values to vary rapidly from picture topicture and cause annoying illumination effects. For instance, assuminga scene with a static background and a sudden flash (like an explosionor fireworks) in the foreground may provide annoying visual artefacts.In such cases, due to the flash, the white W will increase, as well as Mand then the modulation value Ba. When the modulation value Ba is high,the tone-adjustment function suppress the dark more, and this may inducean unexpected sudden darkening of the background in the tone-adjustedpicture. To prevent such an unnatural and annoying temporal variation ofthe luminosity in the tone-adjusted video sequence, temporalstabilization is proposed to smooth the overall luminosity variation ofthe video sequence.

In accordance with an example of the present principles, an exponentialstabilization is used.

Let Ba^(n) be the modulation determined at picture n, and Ba^(t,n) themodulation value after temporal stabilization. The exponential temporalstabilization is then given by:

Ba ^(t,n) =πBa ^(n)+(1−λ)Ba ^(t,n−1)   (17)

with λ a real value adapted to the picture rate.

Other temporal smoothing filters may be used for temporal stabilizingthe modulation values.

In accordance with an example of the principles, the method furthercomprises transmitting the modulation value Ba and possibly the inputparameter highlightGainControl in a bitstream.

For example, the modulation value Ba and possibly the input parameterhighlightGainControl is (are) encoded as a metadata contained in anadhoc SEI message [Technicolor's response to CfE for HDR and WCG(category 1)—Single layer HDR video coding with SDR backwardcompatibility, ISO/IEC JTC1/SC29/WG11 MPEG2014/M36263June 2015, Warsaw,Poland].

In accordance with the present principles, illustrated in FIG. 6, amethod for inverse-tone-mapping a tone-mapped version of an inputpicture I by using a parametric inverse-tone-adjustment function ITAF.Said parametric inverse-tone-adjustment function ITAF is the inverse ofthe tone-adjustment function TAF described above.

Said method for inverse-tone-mapping comprises obtaining a modulationvalue Ba responsive to a brightness level of the input picture I, andobtaining at least one parameter of the inverse-tone-adjustment functionITAF responsive to said modulation value Ba.

In according with an example of the present principle, when the toneadjustment function TAF is defined by equation (1) and its parameters byequations (2), (3) and (4) (first example or one of its variants), theinverse-tone-adjustment function ITAF is obtained as the reciprocalfunction of the tone adjustment function depicted in equation (1) asfollows:

$y = \{ {{\begin{matrix}{{x/{SGC}},} & {0 \leq x \leq {xsgcInv}} \\{{{( {\sqrt{{4\; {ax}} - {4\; {ac}} + b^{2}} - b} )/2}\; a},} & {{xsgcInv} < x < {xhgcInv}} \\{{( {{{x++}{HGC}} - 1} )/{HGC}},} & {{xhgcInv} \leq x \leq 1}\end{matrix}{with}{xsgcInv}} = {{{xsgc}*{SGC}{xhgcInv}} = ( {{{HGC}*{xhgc}} + 1.0 - {HGC}} )}} $

and where SGC, HGC are given by equation (4).

In according with an example of the present principle, when the toneadjustment function TAF is defined by equation (6) (second example)andits parameters by equations (7), (8) and (9), theinverse-tone-adjustment function ITAF is obtained as the reciprocalfunction of the tone adjustment function depicted in equation (8) asfollows:

$y = \{ {{\begin{matrix}{{{{Ba}.x}/{SGC}^{\prime}},} & {0 \leq x \leq {xsgcInv}^{\prime}} \\{{{{{Ba}.( {\sqrt{{4a^{\prime}x} - {4\; a^{\prime}c^{\prime}} + b^{\prime 2}} - b^{\prime}} )}/2}\; a^{\prime}},} & {{xsgcInv}^{\prime} < x < {xhgcInv}^{\prime}} \\{{( {{{Ba}.x} + {HGC}^{\prime} - {{Ba}.}} )/{HGC}^{\prime}},} & {{xhgcInv}^{\prime} \leq x \leq 1}\end{matrix}\mspace{20mu} {with}\mspace{20mu} {xsgcInv}^{\prime}} = {{{xsgc}^{\prime}*\frac{{SGC}^{\prime}}{Ba}\mspace{20mu} {xhgcInv}^{\prime}} = \frac{{{HGC}^{\prime}*{xhgc}^{\prime}} + {Ba} - {HGC}^{\prime}}{Ba}}} $

and where SGC′, HGC′ are given by equation (9).

In according with an example of the present principles, when the toneadjustment function is defined by equation (7) (third example), theinverse-tone-adjustment function ITAF is defined as follows:

ba _(N) =Ba/PeakL

N=log(1+1/(k. ba_N))

InverseToneAdjustment(x)=k. ba _(N).(e ^(x.N)−1), ∀X ∈ [0,1]

The tone-adjustment function (and inverse-tone-adjustment function) maybe used in any encoding/decoding scheme that requires a tone-mapping(inverse-tone-mapping) processing.

For example, The HDR/WCG encoding/decoding scheme as requires by theMpeg HDR/WCG Call For Evidence (Call for Evidence (CfE) for HDR and WCGVideo Coding, ISO/IEC JTC1/SC29/WG11 MPEG2014/N15083, February 2015,Geneva, Switzerland) defines two types of requirements. First type isHDR compression performance, i.e. HDR visual quality as a function ofthe coded bitrate. Second type of requirement is backward compatibility,i.e. the ability to provide a compressed video bit-stream that can bedecoded and displayed with existing legacy equipment, while provided anSDR (Standard Dynamic Range) picture (video) that is viewable as is,without any further processing.

FIG. 7 illustrates the overall method for encoding HDR content whichprovides both HDR compression and SDR backward compatibility features(Philips HDR proposal Dynamic range conversion in relation to the“Unified Model” as discussed in SMPTE DG “Dynamic Metadata for ColorTransforms of HDR and WCG Images” R. Nijland Koninklijke Philips N.V.20150421).

The method comprises a dynamic conversion step 100, which transforms theinput linear HDR (R_(HDR),G_(HDR),B_(HDR)) picture, into a SDR linearRGB picture, noted (R_(SDR),G_(SDR),B_(SDR)). The input HDR picture islinear light, with a peak luminance preferably given by MasteringDisplay Max Lum metadata (SMPTE ST 2086). The output(R_(SDR),G_(SDR),B_(SDR)) linear light picture is SDR, hence has a peakluminance equal to 100 nits. Next steps consist in gamma correcting(step 110), conforming to inverse EOTF of recommendation 1886, colorspace transforming (step 120), which provides Y′CbCr output picturewhich is encoded into a coded video stream F (step 130).

FIG. 8 illustrates the overall method for decoding HDR content.

The method comprises decoding a coded video stream F to obtain a decodedY′CbCr picture (step 200), an inverse color space transforming (step210), which provides R′G′B′ picture from a decoded Y′CbCr picture, aninverse gamma correcting (step 220) to obtain a SDR linear RGB picturefrom the R′G′B′ picture, and an inverse dynamic reduction (step 230),which transforms the SDR linear RGB picture, noted(R_(SDR),G_(SDR),B_(SDR)) into the input HDR picture, notes(R_(HDR),G_(HDR),B_(HDR)). The steps 210, 220 and 230 execute reciprocaloperations of the steps 120, 110 and 100 respectively.

FIG. 9 shows the sub-steps of the dynamic range conversion (step 100).

As can be seen, the step 100 consists, for each pixel p of the inputpicture, in computing (step 300) a maximum value T(p) from the componentvalues of each pixel of the input HDR picture (α. R_(HDR), β. G_(HDR),γ. B_(HDR), γ. Y_(HDR)) where (α, β, γ, δ) are fixed weighting factors,typically all equal to 1, obtaining (step 310) a linear value t(p) bytone mapping said maximum value T(p), and multiplying (step 320) thecomponent values of each pixel p of the input HDR picture by a ratio

${w(p)} = \frac{t(p)}{T(p)}$

between the linear value t(p) over the maximum value T(p).

Then the ratio is computed and commonly applied as a multiplicative tonemapping factor onto input (R_(HDR), G_(HDR), B_(HDR)) component values,to provide linear light tone mapped RGB values:

$\begin{pmatrix}R_{SDR} \\G_{SDR} \\B_{SDR}\end{pmatrix} = {{w(p)} \cdot \begin{pmatrix}R_{HDR} \\G_{HRD} \\B_{HDR}\end{pmatrix}}$

FIG. 10 shows the sub-steps of the inverse dynamic range reduction (step230).

As can be seen, the step 230 consists in obtaining computing (step 400)a maximum value t(p) from the component values of each pixel of the SDRlinear RGB picture, noted (R_(SDR),G_(SDR),B_(SDR)), obtaining (step410) a non-linear value T(p) by inverse-tone mapping the maximum valuet(p), and multiplying (step 420) the component values of each pixel ofthe decoded Y′CbCr picture by a ratio

${w(p)}^{- 1} = \frac{T(p)}{t(p)}$

between the non-linear value T(p) over the maximum value t(p).

FIG. 11 shows a diagram of the steps of obtaining (step 410) a linearvalue t(p) by tone mapping a maximum value T(p) in accordance with anexample of the present principles.

In step 500, a non-linear value nt(p) is obtained by transferring thelinear value t(p) into a non-linear perceptual domain. To do that, aperceptual curve is used, for instance inverse EOTF of recommendationSMPTE 2084 (High

Dynamic Range Electro-Optical Transfer Function of Mastering ReferenceST 2084:2014), or the transfer function proposed by Philips in (PhilipsHDR proposal Dynamic range conversion in relation to the “Unified Model”as discussed in SMPTE DG “Dynamic Metadata for Color Transforms of HDRand WCG Images” R. Nijland Koninklijke Philips N.V. 20150421).

In step 520, the non-linear value nt(p) is reshaped so as to adapt it tothe desired brightness or darkness level of the output picture(R_(SDR),G_(SDR),B_(SDR)). This is the so-called “Local SlopeAdjustment” process which allows producing an output SDR tone mappedpicture with a desired level of brightness for backward compatibilitymatters. In other words, the higher the curve, the brighter the producedSDR picture. Moreover, the SDR picture gets darker when the Local SlopeAdjustment curve gets closer to the Identity function (∀x ∈ [0,1],f(x)=x).

According to the present principles, the “Local Slope Adjustment”process uses the tone-mapping as described in relation with FIGS. 1-5.In other words, the “Local Slope Adjustment” process employs a toneadjustment function parametrized by parameters that need to be chosen.According to the present principles, at least one parameter of the LocalSlope Adjustment curve is responsive to a modulation value, itselfresponsive the brightness level of the input picture as described above.This is a simplified way to parametrize (hence configure and tune) atone adjustment process within a HDR video compression chain thatincludes HDR-to-SDR tone mapping, where the mapped SDR picture isintended to be backward compatible with legacy displays. This furtherprovides way to derive automatically a good SDR backward compatiblepicture, while keeping good compression efficiency.

In step 530, the linear value t(p) is obtained by applying the inverseof the perceptual transfer function to the non-linear value nt(p). Theinverse of the perceptual transfer function is configured with an outputpeak luminance equal to 100 nits.

The decoder 200 is configured to decode data which have been encoded bythe encoder 130. The encoder 130 (and decoder 200) may be block-basedprocessing.

The encoder 130 (and decoder 200) is not limited to a specificencoder/decoder which may be, for example, an image/video coder withloss like JPEG, JPEG2000, MPEG2, HEVC recommendation (“High EfficiencyVideo Coding”, SERIES H: AUDIOVISUAL AND MULTIMEDIA SYSTEMS,Recommendation ITU-T H.265, Telecommunication Standardization Sector ofITU, April 2013) or H264/AVC recommendation (“Advanced video coding forgeneric audiovisual Services”, SERIES H: AUDIOVISUAL AND MULTIMEDIASYSTEMS, Recommendation ITU-T H.264, Telecommunication StandardizationSector of ITU, February 2014)).

On FIG. 1-11, the modules are functional units, which may or not be inrelation with distinguishable physical units. For example, these modulesor some of them may be brought together in a unique component orcircuit, or contribute to functionalities of a software. A contrario,some modules may potentially be composed of separate physical entities.The apparatus which are compatible with the present principles areimplemented using either pure hardware, for example using dedicatedhardware such ASIC or FPGA or VLSI, respectively <<Application SpecificIntegrated Circuit>>, <<Field-Programmable Gate Array>>, <<Very LargeScale Integration>>, or from several integrated electronic componentsembedded in a device or from a blend of hardware and softwarecomponents.

FIG. 12 represents an exemplary architecture of a device 1200 which maybe configured to implement a method described in relation with FIG.1-11.

Device 1200 comprises following elements that are linked together by adata and address bus 1201:

-   -   a microprocessor 1202 (or CPU), which is, for example, a DSP (or        Digital Signal Processor);    -   a ROM (or Read Only Memory) 1203;    -   a RAM (or Random Access Memory) 1204;    -   an I/O interface 1205 for reception of data to transmit, from an        application; and    -   a battery 1206

In accordance with an example, the battery 1206 is external to thedevice. In each of mentioned memory, the word <<register>> used in thespecification can correspond to area of small capacity (some bits) or tovery large area (e.g. a whole program or large amount of received ordecoded data). The ROM 1203 comprises at least a program and parameters.The ROM 1203 may store algorithms and instructions to perform techniquesin accordance with present principles. When switched on, the CPU 1202uploads the program in the RAM and executes the correspondinginstructions.

RAM 1204 comprises, in a register, the program executed by the CPU 1202and uploaded after switch on of the device 1200, input data in aregister, intermediate data in different states of the method in aregister, and other variables used for the execution of the method in aregister.

The implementations described herein may be implemented in, for example,a method or a process, an apparatus, a software program, a data stream,or a signal. Even if only discussed in the context of a single form ofimplementation (for example, discussed only as a method or a device),the implementation of features discussed may also be implemented inother forms (for example a program). An apparatus may be implemented in,for example, appropriate hardware, software, and firmware. The methodsmay be implemented in, for example, an apparatus such as, for example, aprocessor, which refers to processing devices in general, including, forexample, a computer, a microprocessor, an integrated circuit, or aprogrammable logic device. Processors also include communicationdevices, such as, for example, computers, cell phones, portable/personaldigital assistants (“PDAs”), and other devices that facilitatecommunication of information between end-users.

In accordance with an example of encoding or an encoder, the picture Iis obtained from a source. For example, the source belongs to a setcomprising:

-   -   a local memory (1203 or 1204), e.g. a video memory or a RAM (or

Random Access Memory), a flash memory, a ROM (or Read Only Memory), ahard disk;

-   -   a storage interface (1205), e.g. an interface with a mass        storage, a RAM, a flash memory, a ROM, an optical disc or a        magnetic support;    -   a communication interface (1205), e.g. a wireline interface (for        example a bus interface, a wide area network interface, a local        area network interface) or a wireless interface (such as a IEEE        802.11 interface or a Bluetooth® interface); and    -   an picture capturing circuit (e.g. a sensor such as, for        example, a CCD (or Charge-Coupled Device) or CMOS (or        Complementary Metal-Oxide-Semiconductor)).

In accordance with an example of the decoding or a decoder, the decodedpicture Î is sent to a destination; specifically, the destinationbelongs to a set comprising:

-   -   a local memory (1203 or 1204), e.g. a video memory or a RAM, a        flash memory, a hard disk;    -   a storage interface (1205), e.g. an interface with a mass        storage, a RAM, a flash memory, a ROM, an optical disc or a        magnetic support;    -   a communication interface (1205), e.g. a wireline interface (for        example a bus interface (e.g. USB (or Universal Serial Bus)), a        wide area network interface, a local area network interface, a        HDMI (High Definition Multimedia Interface) interface) or a        wireless interface (such as a IEEE 802.11 interface, WiFi® or a        Bluetooth® interface); and    -   a display.

In accordance with examples of encoding or encoder, the coded videostream F is sent to a destination. As an example, the stream F is storedin a local or remote memory, e.g. a video memory (1204) or a RAM (1204),a hard disk (1203). In a variant, one or both bitstreams are sent to astorage interface (1205), e.g. an interface with a mass storage, a flashmemory, ROM, an optical disc or a magnetic support and/or transmittedover a communication interface (1205), e.g. an interface to a point topoint link, a communication bus, a point to multipoint link or abroadcast network.

In accordance with examples of decoding or decoder, the stream F isobtained from a source. Exemplarily, the stream is read from a localmemory, e.g. a video memory (1204), a RAM (1204), a ROM (1203), a flashmemory (1203) or a hard disk (1203). In a variant, the bitstream isreceived from a storage interface (1205), e.g. an interface with a massstorage, a RAM, a ROM, a flash memory, an optical disc or a magneticsupport and/or received from a communication interface (1205), e.g. aninterface to a point to point link, a bus, a point to multipoint link ora broadcast network.

In accordance with examples, device 1200 being configured to implement amethod described in relation with FIG. 1-6, belongs to a set comprising:

-   -   a mobile device;    -   a communication device;    -   a game device;    -   a tablet (or tablet computer);    -   a laptop;    -   a still picture camera;    -   a video camera;    -   an encoding chip;    -   a still picture server; and    -   a video server (e.g. a broadcast server, a video-on-demand        server or a web server).

In accordance with examples, device 1200 being configured to implementan encoding method described in relation with FIG. 7, 9 or 11, belongsto a set comprising:

-   -   a mobile device;    -   a communication device;    -   a game device;    -   a tablet (or tablet computer);    -   a laptop;    -   a still picture camera;    -   a video camera;    -   an encoding chip;    -   a still picture server; and    -   a video server (e.g. a broadcast server, a video-on-demand        server or a web server).

In accordance with examples, device 60 being configured to implement adecoding method described in relation with FIG. 8 or 10, belongs to aset comprising:

-   -   a mobile device;    -   a communication device;    -   a game device;    -   a set top box;    -   a TV set;    -   a tablet (or tablet computer);    -   a laptop;    -   a display and    -   a decoding chip.

According to an example of the present principles, illustrated in FIG.13, in a transmission context between two remote devices A and B over acommunication network NET, the device A comprises a processor inrelation with memory RAM and ROM which are configured to implement amethod for encoding an picture as described in relation with the FIG. 7and the device B comprises a processor in relation with memory RAM andROM which are configured to implement which are configured to implementa method for decoding as described in relation with FIG. 8.

In accordance with an example, the network is a broadcast network,adapted to broadcast still pictures or video pictures from device A todecoding devices including the device B.

A signal, intended to be transmitted by the device A, carries the streamF. The stream F comprises a modulation value Ba responsive to abrightness level of the input picture and intended to be used todetermine a parameter of an inverse-tone-mapping method as explainedbefore. Optionally, The stream F further comprises the input parameterhighlightGainControl.

FIG. 14 shows an example of an example of the syntax of such a signalwhen the data are transmitted over a packet-based transmission protocol.Each transmitted packet P comprises a header H and a payload PAYLOAD. Abit of the header H, for example, is dedicated to represent theinformation data indicating that the encoded luminance block representsthe sum of the luminance component of a picture block and arepresentation of an average value of said luminance component.

Implementations of the various processes and features described hereinmay be embodied in a variety of different equipment or applications.Examples of such equipment include an encoder, a decoder, apost-processor processing output from a decoder, a pre-processorproviding input to an encoder, a video coder, a video decoder, a videocodec, a web server, a set-top box, a laptop, a personal computer, acell phone, a PDA, and any other device for processing a picture or avideo or other communication devices. As should be clear, the equipmentmay be mobile and even installed in a mobile vehicle.

Additionally, the methods may be implemented by instructions beingperformed by a processor, and such instructions (and/or data valuesproduced by an implementation) may be stored on a computer readablestorage medium. A computer readable storage medium can take the form ofa computer readable program product embodied in one or more computerreadable medium(s) and having computer readable program code embodiedthereon that is executable by a computer. A computer readable storagemedium as used herein is considered a non-transitory storage mediumgiven the inherent capability to store the information therein as wellas the inherent capability to provide retrieval of the informationtherefrom. A computer readable storage medium can be, for example, butis not limited to, an electronic, magnetic, optical, electromagnetic,infrared, or semiconductor system, apparatus, or device, or any suitablecombination of the foregoing. It is to be appreciated that thefollowing, while providing more specific examples of computer readablestorage mediums to which the present principles can be applied, ismerely an illustrative and not exhaustive listing as is readilyappreciated by one of ordinary skill in the art: a portable computerdiskette; a hard disk; a read-only memory (ROM); an erasableprogrammable read-only memory (EPROM or Flash memory); a portablecompact disc read-only memory (CD-ROM); an optical storage device; amagnetic storage device; or any suitable combination of the foregoing.

The instructions may form an application program tangibly embodied on aprocessor-readable medium.

Instructions may be, for example, in hardware, firmware, software, or acombination. Instructions may be found in, for example, an operatingsystem, a separate application, or a combination of the two. A processormay be characterized, therefore, as, for example, both a deviceconfigured to carry out a process and a device that includes aprocessor-readable medium (such as a storage device) having instructionsfor carrying out a process. Further, a processor-readable medium maystore, in addition to or in lieu of instructions, data values producedby an implementation.

As will be evident to one of skill in the art, implementations mayproduce a variety of signals formatted to carry information that may be,for example, stored or transmitted. The information may include, forexample, instructions for performing a method, or data produced by oneof the described implementations. For example, a signal may be formattedto carry as data the rules for writing or reading the syntax of adescribed example of the present principles, or to carry as data theactual syntax-values written by a described example of the presentprinciples. Such a signal may be formatted, for example, as anelectromagnetic wave (for example, using a radio frequency portion ofspectrum) or as a baseband signal. The formatting may include, forexample, encoding a data stream and modulating a carrier with theencoded data stream. The information that the signal carries may be, forexample, analog or digital information. The signal may be transmittedover a variety of different wired or wireless links, as is known. Thesignal may be stored on a processor-readable medium.

A number of implementations have been described. Nevertheless, it willbe understood that various modifications may be made. For example,elements of different implementations may be combined, supplemented,modified, or removed to produce other implementations. Additionally, oneof ordinary skill will understand that other structures and processesmay be substituted for those disclosed and the resulting implementationswill perform at least substantially the same function(s), in at leastsubstantially the same way(s), to achieve at least substantially thesame result(s) as the implementations disclosed. Accordingly, these andother implementations are contemplated by this application.

1. A method for tone-mapping an input picture by using a parametrictone-adjustment function defined over multiple ranges, at least oneparameter of the tone-adjustment function being associated to eachrange, wherein the method comprises defining a non-linear toneadjustment function over at least one range, and determining a parameterof said tone-adjustment function modulated by according to a decreasingconvex function taking into account a brightness level of the inputpicture.
 2. The method of claim 1, wherein the method also comprisesdetermining another parameter of said tone-adjustment function accordingto an increasing concave function taking into account a brightness levelof the input picture.
 3. The method of claim 2, wherein the toneadjustment function is linear over a first range, parabolic over asecond range and linear over a third range.
 4. The method of claim 3,wherein the tone adjustment function is defined: over the first rangeby:y=SGC*x with SGC a real parameter value, y an output value and x aninput value; over the second range by:ax ² +b+x+c, x _(SGC) <x<x _(HGC) over the third range by:y=HGC*x+(1−HGC) with HGC a slope; where $\{ {\begin{matrix}{a = {{{- 0.5} \cdot {SGC}} - {{HGC}\mspace{14mu} {MTA}}}} \\{b = {\frac{1 - {HGC}}{MTA} + \frac{{SGC} + {HGC}}{2}}} \\{c = {\frac{1 - {HGC}}{{SGC} - {HGC}} + \frac{MTA}{2}}}\end{matrix}\{ \begin{matrix}{x_{SGC} = {\frac{1 - {HGC}}{{SGC} - {HGC}} - \frac{MTA}{2}}} \\{x_{HGC} = {\frac{1 - {HGC}}{{SGC} - {HGC}} + \frac{MTA}{2}}}\end{matrix} } $ with MTA, a real parameter value and$\quad\{ {{\begin{matrix}{{{exposure} = {\frac{shadowGainControl}{4} + 0}},5} \\{{expgain} = {{v( \frac{L_{source}}{L_{target}} )}\mspace{14mu} {with}\mspace{14mu} v\mspace{14mu} a\mspace{14mu} {function}\mspace{14mu} {based}\mspace{14mu} {on}\mspace{14mu} L_{target}}} \\{{SGC} = {{expgain}.{exposure}}} \\{{HGC} = \frac{highLightGainControl}{4}} \\{{MTA} = \frac{midTonesAdjustment}{2}}\end{matrix}{with}\mspace{14mu} {v(x)}} = {{\frac{\log ( {1 + {( {\rho - 1} ).x^{\frac{1}{\gamma}}}} )}{\log (\rho)}\mspace{14mu} {and}\mspace{14mu} \rho} = {1 + {32.( \frac{L_{target}}{100000} )^{1/\gamma}}}}} $where shadowGainControl, and midTonesAdjustment are real values givenby: $\quad\{ \begin{matrix}{{shadowGainControl} = {0.229 + {2.47*{\exp ( {{- 0.333}*{Ba}} )}}}} \\{{midTonesAdjustment} = {2.21*{\exp ( {{- 0.16}*{Ba}} )}}}\end{matrix} $ where highLightGainControl is a real value and amodulation value Ba responsive to a brightness level of the inputpicture and expressed in nits.
 5. The method of claim 4, wherein thereal value highlightGainControl is a constant value.
 6. The method ofclaim 4, wherein the real value highlightGainControl is kept as anotherparameter in addition to the modulation value.
 7. The method of claim 4,wherein the real value highlightGainControl is given by:highlightGainControl=2'2*exp(−0.26/Ba)
 8. The method of claim 3, whereinthe tone adjustment function is defined: over the first range by:$y = {{SGC}^{\prime}*\frac{x}{Ba}}$ with SGC a real parameter value, yan output value and x an input value; over the second range by:$y = {{a^{\prime}( \frac{x}{Ba} )}^{2} + {b^{\prime}\frac{x}{Ba}} + c^{\prime}}$over the third range by:$y = {{{HGC}^{\prime}*\frac{x}{Ba}} + ( {1 - \frac{{HGC}^{\prime}}{Ba}} )}$with HGC a slope; where $\{ {\begin{matrix}{a^{\prime} = {{Ba}.( {{{- 0.5} \cdot {SGC}^{\prime}} - {{HGC}^{\prime}.\mspace{14mu} {MTA}^{\prime}}} )}} \\{b^{\prime} = {\frac{{Ba} - {HGC}^{\prime}}{{MTA}^{\prime}} + \frac{{SGC}^{\prime} + {HGC}^{\prime}}{2}}} \\{c^{\prime} = {\frac{{Ba} - {HGC}^{\prime}}{{SGC}^{\prime} - {HGC}^{\prime}} + \frac{{MTA}^{\prime}}{2}}}\end{matrix}\{ \begin{matrix}{x_{SGC}^{\prime} = {\frac{B_{a} - {HGC}^{\prime}}{{SGC}^{\prime} - {HGC}^{\prime}} - \frac{{MTA}^{\prime}}{2}}} \\{x_{HGC}^{\prime} = {\frac{B_{a} - {HGC}^{\prime}}{{SGC}^{\prime} - {HGC}^{\prime}} + \frac{{MTA}^{\prime}}{2}}}\end{matrix} } $ with MTA, a real parameter value and$\quad\{ {{\begin{matrix}{{expgain} = {v( \frac{L_{source}}{L_{target}} )}} \\{{SGC}^{\prime} = {expgain}} \\{{HGC}^{\prime} = \frac{highLightGainControl}{4}} \\{{MTA}^{\prime} = \frac{midTonesAdjustment}{2}}\end{matrix}{with}\mspace{14mu} {v(x)}} = {{\frac{\log ( {1 + {( {\rho - 1} ).x^{\frac{1}{\gamma}}}} )}{\log (\rho)}\mspace{14mu} {and}\mspace{14mu} \rho} = {1 + {32.( \frac{L_{target}}{100000} )^{1/\gamma}}}}} $where midTonesAdjustment is a real value given by:$\quad\{ \begin{matrix}{{midTonesAdjustment} = {2.21*{\exp ( {{- 0.16}*{Ba}} )}}} \\{{highlightGainControl} = {CST}}\end{matrix} $ where highlightGainControl is a real value and amodulation value Ba responsive to a brightness level of the inputpicture and expressed in nits.
 9. The method of claim 8, wherein thereal value highlightGainControl is a constant value.
 10. The method ofclaim 8, wherein the real value highlightGainControl is kept as anotherparameter in addition to the modulation value.
 11. The method of claim8, wherein the real value highlightGainControl is given by:highlightGainControl=2−2*exp(−0.26/Ba)
 12. The method of claim 1,wherein the tone-adjustment function is a parametric logarithm functiondefined by: ba_(N) = Ba/PeakL$N = {\log ( {1 + \frac{1}{k.{ba}_{N}}} )}$${y = \frac{\log ( {1 + \frac{x}{k.{ba}_{N}}} )}{N}},{\forall{x \in \lbrack {0,1} \rbrack}}$with k a constant value, y an output value and x an input value andPeakL the peak luminance value of the input picture.
 13. The method ofclaim 4, wherein the modulation value is responsive to a mid-tone levelof the input picture.
 14. The method of claim 13, wherein the mid-tonelevel is determined based on a black level and a white level.
 15. Themethod of claim 14, wherein the mid-tone level is determined as one of(1) a geometric mean and (2) a logarithm mean of the black level and thewhite level.
 16. The method of claim 4, wherein the input image is oneof a plurality of pictures included in a video sequence, and wherein thedetermining of the modulation value is performed for each of theplurality of pictures, wherein the modulation values for the pluralityof pictures are temporally smoothed.
 17. A method forinverse-tone-mapping a tone-mapped version of an input picture by usinga parametric inverse-tone-adjustment function defined over multipleranges, at least one parameter of the tone-adjustment function beingassociated to each range, wherein the method comprises defining anon-linear tone adjustment function over at least one range, andobtaining a parameter of the inverse-tone-adjustment function accordingto a decreasing convex function taking into account a brightness levelof the input picture.
 18. A method for encoding an input picturecomprising: obtaining a maximum value from the component values of theinput picture; obtaining a linear value by tone-mapping said maximumvalue according to a method of claim 1; multiplying the input picture bya ratio between the linear value over the maximum value.
 19. A methodfor decoding a picture comprising: obtaining a maximum value from thecomponent values of a decoded picture; obtaining a non-linear value byinverse-tone-mapping said maximum value according to a method of claim17; multiplying the decoded picture by a ratio between the non-linearvalue over the maximum value.
 20. A device for tone-mapping an inputpicture by using a parametric tone-adjustment function defined overmultiple ranges, at least one parameter of the tone-adjustment functionbeing associated to each range, wherein the device comprises a processorconfigured to define a non-linear tone adjustment function over at leastone range, and to determine a parameter of said tone-adjustment functionaccording to a decreasing convex function taking into account abrightness level of the input picture.
 21. A device for encoding aninput picture comprising a processor configured to: obtain a maximumvalue from the component values of the input picture; obtain a linearvalue by tone-mapping said maximum value according to a method of claim1; multiply the input picture by a ratio between the linear value overthe maximum value.
 22. A device for decoding a picture comprising aprocessor configured to: obtain a maximum value from the componentvalues of a decoded picture; obtain a non-linear value byinverse-tone-mapping said maximum value according to a method of claim17; multiply the decoded picture by a ratio between the non-linear valueover the maximum value.
 23. A non-transitory computer program productcomprising program code instructions to execute the steps of the methodaccording to claim 1 when this program is executed on a computer.
 24. Anon-transitory storage medium carrying instructions of program code forexecuting steps of the method according to claim 1, when said program isexecuted on a computing device.
 25. (canceled)